Colorectal cancer (CRC) is one of the most common cancers in the developed world, and its incidence is continuing to increase. Although the progression of colorectal cancer from benign polyp to adenoma to carcinoma is well studied (1), the molecular events influencing the transition and establishment of metastasis are less well understood. The prognosis and treatment of CRC currently depends on the clinico-pathological stage of disease at the time of diagnosis, and primary surgical treatment. Unfortunately disease stage alone does not allow accurate prediction of outcome for individual patients. If patient outcomes could be predicted more accurately treatments could be tailored to avoid under-treating patients destined to relapse, or over-treating patients who would be helped by surgery alone.
Many attempts have been made to identify markers that predict clinical outcome in CRC. Until recently most studies focused on single proteins or gene mutations with limited success in terms of prognostic information (2). Microarray technology enables the identification of sets of genes, called classifiers or signatures that correlate with cancer outcome. This approach has been applied to a variety of cancers, including CRC (3-5), but methodological problems and a lack of independent validation has cast doubt over the findings (6, 7). Furthermore, doubts about the ability of classifiers/signatures to predict outcome have arisen due to poor concordance of identified by different researchers using different array platforms and methodologies (8).
There is a need for further tools to predict the prognosis of colorectal cancer. This invention provides further methods, compositions, kits, and devices based on prognostic cancer markers, specifically colorectal cancer prognostic markers, to aid in the prognosis and treatment of cancer.